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Transcript of Dissertation
(Murphy and Johnson, 2011; Chemers, 2002) Leadership Variables and hypothesis Identification with a leader Validation from a leader Discrimination Job satisfaction Negative Positive Positive 1 – Discrimination will have a negative impact on employee job satisfaction Hypothesis 2 – Leader identification and validation will have a positive impact on employee job satisfaction Variables and hypothesis Moderation effects DV IV IV Job satisfaction Moderating variable
(Howell, 2013) Discrimination Identification with a leader Validation from a leader Second analysis 3 – Early identification with a leader and validation from a leader will attenuate the negative impact of discrimination on employee job satisfaction Social identity and leadership Research question Participants 33.90 years 58% - 42% Amiot, Blanchard, & Gaudreau, 2008; Amiot, Terry, Wirawan, & Grice, 2010 Newcomer context Design and measures Procedure Informed consent
Free to withdraw
Anonymity was ensured
Fully debriefed Analytic Strategy 1 - Assumptions 2 - Descriptives 3 - Hierarchical moderation regression analysis as per Cohen, Cohen, West and Aiken (2002). Step one Step two T1 Identification
T2 Job satisfaction T1 Identification X T1 discrimination
(Interaction term) Step one Step two T1 Validation
T1 Discrimination T2 Job satisfaction T1 Validation X T1 discrimination
(Interaction term) Preliminary Analysis Two violations:
K-Smirnov - (D(136) = 0.15, p < 0.01)
Skew = 1.3 (width)
Kurtosis = 1.4 (height) 1 - Validation and Identification appeared to be collinear (.81) 2 - Discrimination was not normally distributed Descriptive statistics Identification with a leader Discrimination Job satisfaction Negative: r(134) = -.25, p < .05) Positive: r(136) = .35, p < .01) Positive: r(129) = .31, p < .01) Validation from a leader Main analysis Identification with a leader Discrimination Job satisfaction Not significant: B=-.16, p=.060 Significant: B=.27, p=.002 Identification with a leader The overall model:
R2 = .14, F (3,125) = 6.59, p <.001 Step 1 Step 2 DV IV IV Job satisfaction Moderating variable Discrimination Identification with a leader
B=-.14, p=.118 Model did not account for a significant increase in variance explained: R2ch.=.02, Fch.(3, 125)=2.479, p=.118. Validation from a leader The Overall model:
R2 = .40, F (3,122) = 7.77, p <.001 Discrimination Job satisfaction Not significant: B=-.12, p=.176 Significant: B=.31, p=.001 Validation from a leader Step 1 Step 2 DV IV IV Job satisfaction Moderating variable Discrimination Validation from a leader
B=-.23, p=.05 Model did account for a significant increase in variance explained: R2ch.=.027, Fch.(3, 122)=3.918, p=.05 Decomposition
Both slopes were significant:
High Validation B = -.50, p =.05
Low Validation B = -.33, p <.05 summary of results 1 – Discrimination will have a negative impact on employee job satisfaction
2 – Leader identification and validation will have a positive impact on employee job satisfaction
3 – Early identification with a leader and validation by a leader will attenuate the negative impact of discrimination on employee job satisfaction Testing identification Testing validation Summary of results What this means Critique What this means Validation Identification Antecedent Critique Small effect sizes Discrimination measure